Kevin Small

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Dan RothProfessor of Computer Science, University of PennsylvaniaVerified email at seas.upenn.edu
Thomas TrikalinosHealth Services, Policy & PracticeVerified email at brown.edu
Byron WallaceAssociate Professor, Northeastern UniversityVerified email at ccs.neu.edu
Carla BrodleyNortheastern UniversityVerified email at neu.edu
Alexandre KlementievPrincipal Applied Scientist, Amazon, SeattleVerified email at amazon.com
Li ZhouCarnegie Mellon UniversityVerified email at cs.cmu.edu
Joseph LauBrown UniversityVerified email at brown.edu
Ivan TitovUniversity of Edinburgh / University of AmsterdamVerified email at inf.ed.ac.uk
Christopher H SchmidBrown UniversityVerified email at brown.edu
Xin LiAlibaba, UIUC, YahooVerified email at alibaba-inc.com
Christina M. LillProfessor, University of Münster, Germany; Lecturer, Imperial College London, UKVerified email at uni-luebeck.de
Oleg RokhlenkoAmazonVerified email at amazon.com
Nikhil JohriSoftware Engineering Manager at FacebookVerified email at stanford.edu
Ming-Wei ChangGoogle ResearchVerified email at google.com
Tim VieiraJohns Hopkins UniversityVerified email at cs.jhu.edu
Vivek SrikumarAssociate Professor, School of Computing, University of UtahVerified email at cs.utah.edu
Dan GoldwasserPurdue UniversityVerified email at purdue.edu
Quang DoUniversity of Illinois, FacebookVerified email at fb.com
Gourab KunduUniversity of Illinois at Urbana ChampaignVerified email at illinois.edu
V.G.Vinod VydiswaranAssistant Professor of Learning Health Sciences and of Information, University of MichiganVerified email at umich.edu

Kevin Small

Principal Applied Scientist, Amazon

Verified email at amazon.com - Homepage

machine learning natural language processing artificial intelligence data mining


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Deploying an interactive machine learning system in an evidence-based practice center: abstrackr BC Wallace, K Small, CE Brodley, J Lau, TA Trikalinos Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium …, 2012	458	2012
Class imbalance, redux BC Wallace, K Small, CE Brodley, TA Trikalinos 2011 IEEE 11th International Conference on Data Mining, 754-763, 2011	214	2011
Margin-based active learning for structured output spaces D Roth, K Small European Conference on Machine Learning, 413-424, 2006	144	2006
Active learning for biomedical citation screening BC Wallace, K Small, CE Brodley, TA Trikalinos Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010	135	2010
An unsupervised learning algorithm for rank aggregation A Klementiev, D Roth, K Small European Conference on Machine Learning, 616-623, 2007	124	2007
Unsupervised rank aggregation with distance-based models A Klementiev, D Roth, K Small Proceedings of the 25th international conference on Machine learning, 472-479, 2008	121	2008
Toward modernizing the systematic review pipeline in genetics: efficient updating via data mining BC Wallace, K Small, CE Brodley, J Lau, CH Schmid, L Bertram, CM Lill, ... Genetics in Medicine 14 (7), 663-669, 2012	76	2012
Who should label what? Instance allocation in multiple expert active learning BC Wallace, K Small, CE Brodley, TA Trikalinos Proceedings of the SIAM International Conference on Data Mining (SDM), 2011	76	2011
Multi-domain Dialogue State Tracking as Dynamic Knowledge Graph Enhanced Question Answering L Zhou, K Small arXiv preprint arXiv:1911.06192, 2019	72	2019
Unsupervised rank aggregation with domain-specific expertise A Klementiev, D Roth, K Small, I Titov Twenty-First International Joint Conference on Artificial Intelligence, 2009	72	2009
The constrained weight space svm: learning with ranked features K Small, B Wallace, C Brodley, T Trikalinos the 28th International Conference on Machine Learning (ICML), 2011	59	2011
Relation alignment for textual entailment recognition M Sammons, VGV Vydiswaran, T Vieira, N Johri, MW Chang, ... Text Analysis Conference (TAC), 2009	58	2009
The role of semantic information in learning question classifiers X Li, D Roth, K Small Proceedings of the International Joint Conference on Natural Language Processing, 2004	53	2004
Margin-based active learning for structured predictions K Small, D Roth International Journal of Machine Learning and Cybernetics 1 (1-4), 3-25, 2010	39	2010
Challenges and Opportunities in Applied Machine Learning CE Brodley, U Rebbapragada, K Small, B Wallace AI Magazine 33 (1), 11-24, 2012	35	2012
End-to-end offline goal-oriented dialog policy learning via policy gradient L Zhou, K Small, O Rokhlenko, C Elkan arXiv preprint arXiv:1712.02838, 2017	30	2017
Interactive feature space construction using semantic information D Roth, K Small Proceedings of the Thirteenth Conference on Computational Natural Language …, 2009	29	2009
Methods for the joint meta‐analysis of multiple tests TA Trikalinos, DC Hoaglin, KM Small, N Terrin, CH Schmid Research Synthesis Methods 5 (4), 294-312, 2014	28	2014
Modeling annotation time to reduce workload in comparative effectiveness reviews BC Wallace, K Small, CE Brodley, J Lau, TA Trikalinos Proceedings of the 1st ACM International Health Informatics Symposium, 28-35, 2010	26	2010
Active learning for pipeline models D Roth, K Small Proceedings of the National Conference on Artificial Intelligence (AAAI …, 2008	24	2008

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